Neuromorphic computing, which mimics the human brain’s architecture and function, can be leveraged in edge computing to improve power efficiency, speed, and adaptability.

Automatic foliar spot detection from low-cost RGB digital images using a hybrid approach of convolutional neural network and random forest classifier ...

In light of this, we have developed a recognition model for UAV using a dual-channel multi-scale convolutional neural network (CNN). This model initially enhances UAV recognition accuracy by ...

Gesture recognition is accomplished by employing a Time-of-Flight (ToF) camera and deep neural networks that process 3D point cloud data. The networks achieve an average recognition accuracy exceeding ...

CNN transfer learning methodology is employed by using convolutional layers to train a neural network with a training set of data containing OCT images (Wang et al., 2021). This work contributes to ...

Then, based on three convolutional neural network algorithms, the coal gangue recognition model is established, and the influence of different complex conditions on coal gangue image recognition is ...

Keywords: brain-computer interface, electroencephalogram, motor imagery, convolutional neural networks, brain network analysis Citation: Fan C, Yang B, Li X and Zan P (2023) Temporal-frequency-phase ...